Machine Learning Basics: Building Regression Model in Python

Description

In this course, you will :

• Learn how to solve real life problem using the Linear Regression technique
• Preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression
• Predict future outcomes basis past data by implementing Simplest Machine Learning algorithm
• Understand how to interpret the result of Linear Regression model and translate them into actionable insight
• Understanding of basics of statistics and concepts of Machine Learning
• Indepth knowledge of data collection and data preprocessing for Machine Learning Linear Regression problem
• Learn advanced variations of OLS method of Linear Regression
• Course contains a end-to-end DIY project to implement your learnings from the lectures
• How to convert business problem into a Machine learning Linear Regression problem
• Basic statistics using Numpy library in Python
• Data representation using Seaborn library in Python
• Linear Regression technique of Machine Learning using Scikit Learn and Statsmodel libraries of Python

Syllabus :

• Setting up Python and Jupyter Notebook​​​​​​​
• Basics of Statistics​​​​​​​
• Introduction to Machine Learning​​​​​​​
• Data Preprocessing​​​​​​​
• Linear Regression​​​​​​​